BREEDIT: A novel multiplex genome editing strategy to improve complex quantitative traits in maize (Zea mays L.)
Christian Damian LorenzoiD, Kévin DebrayiD, Denia HerweghiD, Ward DeveltereiD, Lennert ImpensiD, Dries SchaumontiD, Wout VandeputteiD, Stijn AesaertiD, Griet CoussensiD, Yara de BoeiD, Kirin DemuynckiD, Tom Van HautegemiD, Laurens PauwelsiD, Thomas B. JacobsiD, Tom RuttinkiD, Hilde NelisseniD, Dirk InzéiD
Abstract
Ensuring food security for an ever-growing global population while adapting to climate change is the main challenge for agriculture in the 21st century. Though new technologies are being applied to tackle the problem, we are approaching a plateau in crop improvement using conventional breeding. Recent advances in gene engineering via the CRISPR/Cas technology pave the way to accelerate plant breeding and meet this increasing demand. Here, we present a gene discovery pipeline named BREEDIT that combines multiplex genome editing of whole gene families with crossing schemes to improve complex traits such as yield and drought resistance. We induced gene knockouts in 48 growth-related genes using CRISPR/Cas9 and generated a collection of over 1000 gene-edited maize plants. Edited populations displayed, on average, significant increases of 5 to 10% for leaf length and up to 20% for leaf width compared with controls. For each gene family, edits in subsets of genes could be associated with increased traits, allowing us to reduce the gene space needed to focus on for trait improvement. We propose BREEDIT as a gene discovery pipeline which can be rapidly applied to generate a diverse collection of mutants to identify subsets of promising candidates that could be later incorporated in breeding programs.
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